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Cache and Energy Efficiency of Sparse Matrix-Vector Multiplication for Different BLAS Numerical Types with the RSB Format
Michele Martone
193 - 202
10.3233/978-1-61499-381-0-193
Advances in Parallel Computing
Volume 25: Parallel Computing: Accelerating Computational Science and Engineering (CSE)
Abstract

On a “Sandy Bridge E5-2670” CPU, we compare different performance metrics (speed, energy, cache traffic) of two multi-threaded Sparse Matrix-Vector Multiplication implementations: Intel MKL's CSR and librsb's RSB. We find out primarily that the benefit of RSB over MKL's CSR varies substantially depending on the numerical type (12–40%). We also confirm other studies' results in that energy savings are strongly correlated with fast code, and that memory traffic minimization is the primary performance factor.

$35.00 / €27.50 / £22.00
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